January 2015

In a book that has about 350 pages, the first 250 odd pages are devoted to probability, ODEs and difference equations. The last part of the book covers queuing theory for specific systems, i.e, Poisson arrivals, exponential service times of one or more servers. The most painful thing about this book is that there are innumerable typos. A book that is riddled with typos on almost every other page cannot be an appealing text for an undergrad. My guess is that, this book will be never make it to an undergrad’s study table, unless the authors make a serious effort to publish an errata or come up with a better version of the book. Is there anything good about the book at all ? Well, may be, the chapter on difference equations is worth going over just once. On a second thought, I think that the first 250 pages of the book can be rewritten concisely so that it can be pushed to the appendix. That leaves the last 100 pages of the book that reads more like a cheat sheet rather than a book from which one can really learn something. This book desperately needs a rewrite from the authors,else it is going to languish alongside the books that die silently every year.

This book is a ~160 page tirade against the book “Flash Boys” that has captured everyone’s mindshare with the marketing slogan – ”U.S. stock market is rigged”. The author, Peter Kovac, has worked with a HFT firm for eight years and claims to be an industry insider. Since “Flash Boys” was basically anti-HFT book, it is natural to expect someone from the HFT to criticize the book. So, there we have Peter Kovac with a book length treatment that has similar title with Lewis book but a different tagline.

For a person who has read “Flash Boys”, it is likely that one might be dazzled by Michael Lewis story telling capability. Who doesn’t love a David vs. Goliath story, i.e. Brad &Co vs. Wall Street story? But there is a possibility that one might be too carried away by the arguments in the book. Peter Kovac’s book delves in to the story, strips off the fluff from “Flash Boys” and critically analyzes numbers, examples, arguments, protagonists from the book.

In this post, I will briefly summarize the main points from the book:

Introduction: The Dangers of Speed

The central thesis of “Flash boys” is, “stock exchanges + HFT players+ brokers have rigged the markets”, i.e. intermediaries have screwed investors. However the book does not carry a single interview of a person working in a stock exchange or a HFT firm. If you have read previous books by Michael Lewis, you will see a pattern. He analyzes an event after the fact, picks up a few key people responsible for the event, and writes in great detail about the key people in an entertaining and illuminating way. This book is different and is not an after the fact narration. The underdog who is supposed to have led a revolt is still nowhere near declaring a win. IEX is yet to be granted an exchange status. HFT players are still operating and exchanges have not majorly changed any rules. It looks like Michael Lewis himself succumbed to very element that he criticizes, “speed”, and has gone ahead and published the book, before even seeing whether IEX would really make any difference to the U.S markets or not?

Chapter 1: Spread Networks and the Value of Speed

Since the advent of electronic trading a decade ago, the trading costs and spreads have vastly reduced. The increased speed and automation facilitated more precise prices, and investors have benefited tremendously. Every penny of that reduction in “economic friction” is a cash bonus. Why are market participants still looking to go faster if they can’t make their prices any more precise? The answer is: competition. If they don’t get faster and their competitors do, they lose. Speed doesn’t matter for individual investors, since there is no race to be run. Spread networks story is pretty accurate and the reason people lapped up the service is , speed matters. Lewis claims that intermediaries made between $10B to $22B per year in total profits. How does this stack up to the rest of Wall Street? At this point in his story – early 2010 – Goldman Sachs had just paid $ 16.2 billion to its employees in compensation, out of revenues of $ 45.2 billion for the previous year. In other words, Goldman alone paid more in bonuses and salaries than the total profits of all high-frequency trading firms (plus whoever else he lumped in as “financial intermediaries.”) So, perhaps, they weren’t making “more money than people had ever made on Wall Street.”

Chapter 2: The Education of Brad Katsuyama

Brad starts to suspect the market when the shares of a certain script, Solectron go down as soon as he sells shares. Brad thinks his action should not have caused a price collapse since the firm was going to be acquired and the target price was fixed. The problem with this argument is that the price is never stable even in the case of a merger. There is always a band of traders trying to do “merger arbitrage”. Using the number quoted by Lewis,i.e. $0.0029 per share as the cost of front-running by HFT firms, the author says the money Brad lost was predominantly due to his strategy and not because of front running. It is basic economics 101 playing out where he sells hundreds and thousands of shares increasing the supply that causes the price collapse. Katsuyama’s job was to minimize price impact and when he fails to do that, and ends up blaming HFT traders for front-running his order.

There is a lot of criticism on “maker-taker”model but the key idea behind it simple. When an exchange starts off, it often follows a maker-taker pricing model where a maker is given an incentive to quote. As volumes go up, the exchange may decide to invert the “maker-taker” model and start paying the taker to incentivize access to the markets, in the assumption that the previous players who were paid for providing quotes would still remain as the increased volume would make it lucrative. Sometimes this idea works and sometimes it doesn’t.

The real questions that on must address in this area are:

Fragmentation. By providing another dimension for competition, does this model encourage too many new exchanges? Or does fragmentation occur for other reasons? Would restricting price competition among exchanges impact fragmentation?

Winners and losers. Generally , guys like Katsuyama who take liquidity pay the most under the maker-taker model. If, from a policy perspective, we want to help them at the expense of the market-makers, it makes sense to ban maker-taker. On the other hand, if we don’t want policy to favor one class of traders over another, pricing should be determined by market forces.

Needless complexity. Does the maker-taker model create needless economic complexity in our markets? Or can traders easily account for this in their trading models?

Best execution. Does maker-taker pricing create unhealthy incentives for the “best price” fiduciary responsibility of brokers with respect to their client orders? The fees and rebates flow to the broker, while the price of the shares is passed along to the client.

Instead of addressing the above areas, Lewis messes it up in the book.

Another problem with Brad’s argument is that he believes in the perfect view of market, i.e. if he sees a market at a particular bid and ask, he thinks he can buy or sell as many shares he wants at NBBO. But sadly that is not how markets work. Michael Lewis does criticize flash orders, and rightly so. However the largest critic for flash orders was GETCO, one of the largest HFT players in the world.

“Someone out there was using the fact that stock market orders arrived at different times at different exchanges to front-run orders from one market to another.”

Thor, the tool which Brad and his team used to send orders was a clever tool that foiled the market makers attempt at widening their quotes before a large buy/sell order. When this happens again and again, the only way market makers adjust their quotes is widening their spreads as compared to Pre-Thor days. So, is Thor actually causing market volatility and increased spreads? Will IEX also receive the same response from market makers? Also the whole basis of extrapolating that front running was happening all over U.S markets was based on one trade in citigroup shares. It does not look like a fair extrapolation at all.

Chapter 3: Trying to connect the dots

Colocation

The author dismisses a lot of things that Ronan Ryan describes, such as “moving the server in the colo by three feet” etc., as funny. The guys who moved the server by three feet in the colo center did not have a clue as to why their strategy worked/failed and wanted to come even closer to the main feed from the exchange. Lewis says Ryan is the world authority on colo. But no one has ever heard about him until “Flash boys” got published. There is a reason for the exchanges offering colo, besides the obvious outcome that it generates profits.

Exchange co-location is regulated by the SEC, and, as such, is required to be available to all market participants. Whether or not one thinks it is currently regulated perfectly, it is regulated – thereby providing, if not a guarantee, at least a possibility of fairness. In an exchange data center, the data is broadcast to all traders simultaneously, providing everyone with an equal footing and a fair chance. If exchange co-location were prohibited, traders would still vie to be next to the exchanges. They would just be housed in private data centers, outside the reach of the SEC. Such facilities could discriminate on pricing, or simply establish a monopoly. Any chance at regulation, or fairness, is gone. There would no longer be a common starting line, but instead a system where, unlike today, some firms actually do get a head start. Further, prohibition of co-location would impact the exchanges’ bottom line.

Front running

Any would-be front-runner has to overcome at least five hurdles to rip you off: 1) Determine the price and quantity of shares of your order 2) Buy the same amount of shares you want, before you do 3) Manipulate the market price upward 4) Sell the shares back to you at the higher price 5) Avoid anyone else in the market who could disrupt the scam. With the electronification of the markets last decade and the implementation of Regulation NMS in 2007, the five hurdles above have now become solid barriers to front-running.

Latency Tables

The whole argument of “latency tables” in “Flash boys” falls apart as no order is stamped with a broker name and hence even if a HFT player has a latency table, it would be impossible to tease out whose order was being executed on a specific exchange. If one had a set of perfect latency tables for all algorithms used by all traders at every broker in the market, and all brokers had non-random, precise and unique latencies , one would still never have enough data to figure out who sent an order. Contrary to what Lewis implies, it is utterly impossible to identify anything from a single order on the BATS Exchange. One moment there is nothing. The next moment there is a trade. Nobody knows how long it took the order to hit the BATS Exchange, they only know that a single trade occurred. The next trade on the next exchange isn’t going to be terribly helpful either. One could conceivably measure the difference in time between the trades, but it’s basically useless in identifying anyone since that difference would provide a single data point. Perhaps by the third or fourth exchange one could narrow the field of possible brokers and trading algorithms a bit, but by that time the trade is complete. Remember that all these orders were already in transit anyway, so the whole exercise was pointless to begin with – by the time you saw the first trade report come back, the other orders would be long gone. Lewis completely dodges the question of how any strategy with the help of latency tables, would ever reveal the actual quantity and price of an order. Without this information, there’s no front-running possible.

The example of china ETF order being front-run is a ridiculous example cited in the book. Attributing front-running to such a market behavior is totally unreasonable.

Broker routing orders

Can a HFT firm indulge in front running based on router-driven stock quote of 100 shares on BATS? Impossible, even if a front-runner accurately guessed the quantity of an order, and they fended off all competitors, they are more likely than not to be stuck with a massive losing position as their reward.

Spread Networks – CBSX

The fact that start of Spread networks and SIRI stock volume explosion on CBSX coincided, lead Brad and team to conclude that HFT players were using spread networks to arb. The author attributes the reason to CBSX brilliant decision of using inverse maker-taker pricing for a penny stock because market making in SIRI had an extremely low risk per share. SIRI volumes returned to normalcy when other exchanges followed the same inverse maker-taker model. Which argument to believe is up to you, but the latter sounds far more convincing?

Chapter 4: There’s Another Explanation, but it’s Not As Interesting

RegNMS

Lewis ascribes RegNMS as the main reason for unleashing HFT. However HFT was always present before 2007.The majority of HFT firms trading doesn’t depend upon Regulation NMS, maker-taker pricing, or many of the things that Lewis describes as the foundations of “rigged” markets. Lewis argues that high-frequency trading is bad, and we can fix this if we eliminate co-location, maker -taker pricing, and Regulation NMS’s best execution requirements. But apparently none of these items are necessary for high-frequency trading. If they were eliminated, high-frequency trading would still exist. The only difference would be that big bank equity traders like Katsuyama and friends would have much lower costs (no co-location necessary, much lower trading fees) and much more discretion in obtaining “best execution” for their clients.

SIP

There are three things you need to know about the SIP: 1)You can watch the SIP, you can’t trade on the SIP 2) The SIP is faster than you but slower than other data (it ought to be faster) 3) It is sometimes used for “trade-through” protection, sometimes not. One thing to note is that it is guaranteed to be slower than the markets’ direct data feeds since it must consolidate all the market data from every source. The author says that SIP is just a cheap way to show approximately what the current market is. It’s great for CNBC or your favorite Internet finance site, and probably adequate for any retail investor who doesn’t live next to an exchange and doesn’t possess super-human reflex times. Professional investors have the choice of viewing the SIP or using direct feeds from the exchanges. Anyone who trades frequently will likely chose direct feeds. Lewis uses AAPL stock example to show how slower SIP is advantageous to HFT players. The author systematically makes a case against the AAPL example.

Why Thor needed a regulatory approval ?

As market-makers, they take the risk of always being ready to buy or sell stock. Market-makers will adjust their prices up or down based on risk, and based on supply and demand. If some trader using Thor bought up all the shares on the NYSE, NASDAQ, and BATS , a market-maker on the Boston Stock Exchange would think that (a) this new surge in demand will push the price higher , and (b) my offer to sell at the current price is a big risk since the price is about to shoot higher. While this market-maker is pondering this, Thor hits them, too. For the idea of Thor was, of course, to jump all the market-makers on all the exchanges at the same time, before even the last ones could react to the new price. The fact that some might see this tactic as rather predatory may have been why RBC’s upper management thought it might be a good idea to seek the SEC’s blessing before widely publicizing Thor. Was Thor predatory? The premise of using latency to trick market-makers into bearing the price impact isn’t illegal, but it does seem to prey on a particular weakness of a particular (essential) class of market participant.

Spreads have decreased because of automation

Lewis says spreads have decreased because of computerization, not because of HFT. Sadly, exchanges being computerized do not lead to spread attenuation. It is HFT players who play the role of market makers that have made spreads shrink.

Dark pools – play ground for HFT players

Dark pools don’t disseminate market data to any of their clients, high-frequency or otherwise. Some dark pool operators make no guarantees about their own trading in the dark pool. For those that promise that their bank’s proprietary traders have no special advantages, it’s still blind faith: unlike the public markets, there are few police on this beat. For this reason, many high-frequency traders choose not to trade in dark pools – they are afraid that the banks’ traders will rip them off in the dark.

Chapter 5: Sergey Aleynikov

There isn’t much in this chapter, except that the author says Lewis should have done some more research in the story. Aleynikov’s claimed that he only took open source code. Open source code is readily available on the Internet – that’s the idea behind it. Why didn’t he just plan on re-downloading the code at his new job? It’s difficult to buy the idea that it would be easier for Aleynikov to transfer the files to a third-party server, later retrieve them, and then “disentangle” all the Goldman proprietary code.

Chapter 6: How To Take Billions From Wall Street

The author wishes that IEX succeeds so that people might think that HFT problem is solved in the markets, a problem that did not exist in the first place.

Maker-Taker pricing

The pricing used by IEX – $ 0.0009 per share for takers – is far more attractive to a taker than the pricing on any of the major exchanges. Applying Lewis’ logic, this is just another kickback to the big banks (all of whom are on IEX), and IEX is one big “flash trap.” If it seems logically inconsistent, that’s because it is. Realistically, different pricing models are just that: different pricing models. They are set by the exchange to attract business. To claim that high-frequency puppet-masters dictate these pricing structures to the exchanges doesn’t make sense in the case of IEX, NASDAQ, NYSE, or anyone else.

Types of Predatory behavior

The puzzle masters in “Flash boys” categorize the predatory behavior in to three types. 1) front running, 2) rebate arb, 3) slow market arb. Front running is already shown to be impossible in the earlier chapters. The fact that HFT players can get a rebate without doing a trade is impossible. Also slow market arb is again impossible in the examples cited in the book because of trade-through protection provided by RegNMS.

IEX

It seems that (1) the tweaks implemented by IEX would not actually prevent the predatory trading that Lewis hypothesizes, but (2) there doesn’t appear to be any predatory trading on IEX. This paradox could be explained two ways. Perhaps the predators are simply scared to show their stripes on IEX. Or perhaps the feared predatory trading is rare to non-existent, and it doesn’t matter that IEX’s defenses are illusory.

Dark Pools

Dark pools and broker internalization facilities aren’t unquestionably bad, but it’s hard to make a compelling case for any significant benefit . For professionals in particular, they make it easier to shoot oneself in the foot. For the public, the lack of transparency doesn’t inspire confidence. And for the markets themselves, there is a legitimate question about whether or not they detract from the price discovery process.

Chapter 7: IEX Launches

One of the often cited reasons for taking a stance against HFT players is that they siphon off trades coming from pension funds and such large institutional clients. It might be worth telling all those critics that the same pension funds are also invested in high-frequency trading firms. For example, more than a third of high-frequency trading behemoth KCG / Getco is owned by institutions and mutual funds. CalPERS and CalSTRS, two of the largest pension funds in the country, own stakes in privately held high-frequency firms as part of their private equity portfolio.

This chapter shows so many chinks in Lewis arguments that I did not feel like summarizing as it would have meant basically replicating the whole chapter from the book. After reading this chapter, I was kind of overwhelmed by how much stuff from “Flash boys” was plain wrong.

Chapter 8 : Dinner with Sergy

About Sergy, the author says that a little more effort should have been taken to understand the truth. He says,

I don’t know what was contained in the 500,000 lines of source code that Aleynikov took. I do know that most trading systems use proprietary code for strategies, but rely on open source operating systems and network processing code. This open source software is often modified for the particular network requirements of trading. And these modifications are quite valuable – they make every single order faster or slower , depending on how clever one is. I wish somebody had asked hard questions.

Takeaway :

All the books written by Michael Lewis till date other than “Flash Boys” are after the fact narration. In his previous works, one can see a pattern. He identifies few key characters and weaves an entertaining story along with facts so that readers can easily understand the basic theme. It looks like with “Flash Boys”, he has created a catchy narrative but sadly the foundation of the narrative is weak. Peter Kovac has written a 100,000 word book that basically rips apart almost every argument of “Flash boys” and thus defends HFT’s role in today’s markets. Must read for someone who wants to critically analyze the arguments made in “Flash boys”, that says U.S markets are rigged.

There is a difference between an R user and an R programmer. The former is usually concerned with writing R scripts, using existing R libraries, in order to do data wrangling / model development / back testing or creating an reproducible research document. R programmer on the other hand is usually interested in creating a package / reusable code that can be used by others in his company / by R community.

The author of the book, Hadley Wickham, has been one of the biggest contributors of infrastructure and visualization packages in R. In this book, the author does a splendid job of explaining the nuts and bolts of R, the knowledge that he has gained from spending more than two decades building useful R packages.

Given the title, it is pretty obvious that this should not be someone’s first book. But I think this should be read as soon as you get some good enough idea about R. Delaying too much in reading this book might not be a nice idea. Even if you intend to be a R user and not an R programmer, I think it is worth your while to spend time and effort in working through this book. If you are intend to write your own packages either for internal use or for community use, this book is priceless.

I found the content on “non standard evaluation”, i.e chapters 13 & 14, to be extremely well organized. You probably have to spend a lot of time on stackoverflow / read other’s code to get the kind of understanding you get, from reading these chapters. Most of the initial chapters in the book start with a few teaser questions . The author suggests to the reader that she can skip the chapter if she is comfortable with all the questions. My guess is that, even a seasoned R programmer will find some of these questions tricky/ tough to answer and will start working through most of the initial chapters.

This is not a book that you can read over a weekend or even a fortnight. My guess is it will take at least a month or two to understand and reflect on many gems scattered through out the book . If you have used shiny package for any UI development, reading chapter 15 of the book basically gives a good idea of what happens behind shiny. If you want to write a C++ function to speed up things and want to use R to call the function, you will have to slog through chapter 19 that deals with this aspect comprehensively. There are two chapters on functional programming that explain the powerful features of R.

My favorite chapters in the book are the ones on non-standard evaluation. The thing about R is that it can be used as an interactive language as well as a functional programming language. So, whenever you write your code and want it to be extensible, you need to think about quite a lot of things. Just read the source code of any base R function and you will see that it looks very different. There are many tradeoffs that an R developer has to make. What are they ? Such questions and many more about non-standard programming are thoroughly explained in ~ 50 pages. There are also chapters on memory management, code optimization, that will be of immense use to any R user/ programmer.

I think this book can serve as an excellent guide to anyone wanting to be a better R user / R developer. It has tons of useful references that you might want to go over, if you really want to understand the language at a deeper level.

Michael Lewis starts off by saying that the mental picture of stock market that most people away from Wall Street carry has changed dramatically over the last decade. He claims that his intent of writing this book is to draw a picture that is the new reality of U.S markets.

Hidden in plain sight

Only Michael Lewis can take a “laying a fiber optic cable” story and make it in to a page turner. This chapter talks about Dan Spivey and his efforts to connect Chicago and New York by a line that is as straightlinish as possible. The company formed by Dan Spivey, called “Spread Networks” began work in 2008 and was finally completed in 2010. To get the necessary approvals for constructing the network and selling this network to Wall Street people, Dan partnered with Jim Barksdale, David Barksdale and Larry Tabb. The whole point of the line was to create inside the public markets a private space, accessible only to those willing to pay the tens of millions of dollars in entry fees. Spread Networks first press release was titled,

Round-trip travel time from Chicago to New Jersey has been cut to 13 milliseconds.

Spread Networks set a goal of coming in at under 840 miles and beaten it; the line was 827 miles long. Spread Networks soon found that many Wall Street banks and hedge funds readily signed up for the line. This was an acknowledgement of the new reality of trading, “speed mattered” and it mattered a LOT.

Brad’s problem

Brad Katsuyama

This chapter introduces Brad Katsuyama, an RBC trader and the hero of the book. When Brad gets transferred to Wall Street office, he realizes that the culture on the street is very different from the conservative, team oriented culture he is used to, back in Canada. His real trouble began at the end of 2006, after RBC paid $100 million for a U.S. electronic stock market trading firm called Carlin Financial. There was a clash of cultures between RBC and Carlin. After the subprime crisis, he plans to leave Wall Street for good. However life had different plans for him. RBC severs the relationship with Carlin and Brad becomes the head for electronics trading. Initial thoughts of RBC team members who propose opening a dark pool makes no sense to him and he decides not to get in to dark pools game. As he tried to fix the “electronics trading biz”, he is perplexed with the whole system. He is clueless about certain aspects such as, Why was BATS going for inverse maker-taker model? Why was there a need for a maker-take model at all? The biggest problem that Brad faced when he starts using the “electronic trading systems” is that he never got fills at the prices that the screen showed. Every time he tried hitting the bid or lifting the offer, the market moved as soon as he sent the order. It looked like as though the market had read his mind and moved against him. At first he is not certain where the problem was. He thinks that there is a problem with Carlin’s systems, but soon figures out that traders at many other places were facing the same problem. He assembles a team of technologists and starts doing experiments with some very small size orders. This experimental reveals one surprising fact – When he sends an order to one exchange, the trade happens normally. However when the order is sent to multiple exchanges, only partial fills happen.

He becomes more certain that the stock market was no longer a market. It was a collection of small markets scattered across New Jersey and lower Manhattan. When bids and offers for shares sent to these places arrived at precisely the same moment, the markets acted as markets should. If they arrived even a millisecond apart, the market vanished, and all bets were off. Brad knew that he was being front-run—that some other trader was, in effect, noticing his demand for stock on one exchange and buying it on others in anticipation of selling it to him at a higher price. He’d identified a suspect: high-frequency traders.

Ronan’s problem

Ronan Ryan

This chapter is about Ronan Ryan who starts his career in a telecommunications company and soon lands up at Radianz where he is in charge of selling co-lo services. This is where Ronan learns about the importance of latency to every Wall Street firm. Radianz data center at Jersey city could bring down the latency from 43 milliseconds to 3.8 milliseconds, for a firm in Chicago. By early 2008 Ronan was spending a lot of his time abroad, helping high-frequency traders exploit the Americanization of foreign stock markets. In 2009 he is hired by Brad to work RBC as head of HFT trading. Brad educates Ronan about basic market concepts whereas Ronan imparts the tech stuff that he has learnt through his career. Ronan explains the reason for Brad’s successful order execution at BATS and failure at other exchanges. He also explains the reason for BATS strange policy of paying to take liquidity – BATS orders were leading indicators of what was about to happen at other exchanges. HFT players would quickly buy at other exchanges before everyone else and then sell it to the person who had no latency advantage. Brokers were also incentivized to send order flow to certain exchanges as they received payment and kickbacks

The team at RBC slowly realizes that the only way their orders would not get ripped off by HFT players is to send the orders at approximately same time to all the exchanges so that nobody could game it. For this to happen, they had to build their own network. By the end of 2010, Brad and Ronan met with roughly five hundred professional stock market investors who controlled, among them, many trillions of dollars in assets. They never created a PowerPoint; they never did anything more formal than sit down and tell people everything they knew in plain English. Then there was flash crash and Brad’s ideas were in demand.

Another incident happened in September, 2010; a sleepy stock exchange called the CBSX switched to inverted maker-taker model and its trading volume skyrocketed. Ronan and Brad put their heads together and figured out that this was another classic case of ripping off money from investors.Spread Networks had flipped its switch and turned itself on just two weeks earlier. CBSX then inverted its pricing. By inverting its pricing—by paying brokers to execute customers’ trades for which they would normally be charged a fee—the exchange enticed the brokers to send their customers’ orders to the CBSX so that they might be front-run back to New Jersey by high-frequency traders using Spread Networks. The information that high-frequency traders gleaned from trading with investors in Chicago they could use back in the markets in New Jersey. It was now very much worth it to them to pay the CBSX to “make” liquidity. It was exactly the game they had played on BATS, of enticing brokers to reveal their customers’ intentions so that they might exploit them elsewhere. But racing a customer order from Weehawken to other points in New Jersey was hard compared to racing it from Chicago on Spread’s new line.

Tracking the predator

John Schwall

Brad’s next hire was John Schwall and this chapter talks briefly about his background. Schwall started out his work at Bank of America. After Bank Am took over Merrill Lynch during financial crisis, Schwall decided to move to RBC. Schwall knew a lot about RegNMS and could clearly understand the way HFT players played the SIP game. NBBO calculation at the centralized server was slower than that of HFT players and this gave to massive arb opportunities for all those who had faster connectivity. Schwall goes through a ton of LinkedIn profiles and figures out that all the dark pools have HFT players as their clientele. By diverting the client’s order flow in to their dark pools, the brokers were ripping of their client. In return HFT players paid a ton of money for doing this.

Putting a face on HFT

Sergey Aleynikov

This chapter narrates the story of Sergey Aleynikov, who is given 8 years of imprisonment for stealing HFT strategy code from Goldman. Much before this book went to the press, there was an article in Vanity Fair, titled, “Did Goldman Sachs Overstep in Criminally Charging Its Ex-Programmer ?”, that has most of the stuff from this chapter. Michael Lewis pieces together Sergey’s childhood, his career at a telecommunications firm , his programming job Goldman and says

Thus the only Goldman Sachs employee arrested by the FBI in the aftermath of a financial crisis Goldman had done so much to fuel was the employee Goldman asked the FBI to arrest.

How to take billions from Wall Street

This chapter talks about how Brad quits his job at RBC, assembles a team to build an exchange, IEX(Investors Exchange), whose philosophy was to save the investor from getting ripped off by financial intermediaries. Ironically, in his fund raising efforts, he had to feign that he was greedy and only then he could manage to hold potential investors attention. By mid-December he’d sewn up $9.4 million from nine different big money managers. Six months later he’d raise $15 million from four new investors. The money Brad needed that he didn’t get he kicked in himself: By January 1, 2013, he’d put his life savings on the line. At the same time, he went looking for people: software developers and hardware engineers. Brad hired Don Bollerman who had spent 7 years at NASDAQ and had seen it all – a sleepy exchange that turned in to HFT player’s favorite ground.

IEX goal was not to exterminate the hyenas and the vultures but, more subtly, to eliminate the opportunity for the kill. To do that, they needed to figure out the ways that the financial ecosystem favored predators over their prey. Brad hired Dan Aisen and Francis Chung who were ace puzzle crackers in the literal sense of it. Brad also hired Constantine Sokoloff(Matching engine specialist from NASDAQ) to mentor the puzzle masters. The team at IEX got to work and started by analyzing various order types. The more analyzed the order types, they found that almost every fancy order type was meant to rip off investors. The team created a taxonomy of predatory behavior in the stock market. The first they called “electronic front-running”—seeing an investor trying to do something in one place and racing him to the next. (What had happened to Brad, when he traded at RBC.) The second they called “rebate arbitrage”—using the new complexity to game the seizing of whatever kickbacks the exchange offered without actually providing the liquidity that the kickback was presumably meant to entice. The third, and probably by far the most widespread, they called “slow market arbitrage.” This occurred when a high-frequency trader was able to see the price of a stock change on one exchange, and pick off orders sitting on other exchanges, before the exchanges were able to react.

The team at IEX wanted to create an exchange where all the predatory behavior could be attacked. They came up with a brilliant idea. Have their matching engine very far away from the place the broker’s point of presence. They zeroed on making a 350 millisecond delay between the point of presence and matching engine and this they achieved by merely coiling the wire innumerable times (another simple yet damn effective way to INCREASE latency). At the same time, IEX laid its infrastructure in such that it was the fastest to reach other exchanges.

Despite this wonderful idea and infrastructure, they faced one big problem – How should they generate order flow for the exchange by playing a fair game?

An army of one

The last section of the book goes through the struggles that IEX faces in building order flow. One big success comes their way when they manage to sign up Goldman Sachs and in fact on one of trading days, their volume exceeds that of AMEX.

What has happened to IEX since Flash Boys success?

IEX has grown rapidly in 2014. Its daily trading volume has tripled since the first quarter and participant volume has exceeded 100 million shares per day. It is seeking regulatory approval to become a full-fledged stock exchange. If IEX manages to grow its trading volume and its business, it can be a great transformation to the U.S markets.

This book can be savored by anyone who loves silence and solitude. Solitude, in most of our lives, visits us when we are least prepared – unexpected work assignment to a different city/country, sudden hospitalization for an extended period of time, death of partner, break up etc. Most of us are ill-prepared to handle the sudden intrusion of solitude. This coupled with our childhood experiences of hyper protective parents questioning us – “Kid, you are very silent. Is everything OK with you?”— creates an unhealthy attitude towards situations where we are silent and alone.

For most part of my life I have lived alone and have enjoyed it. My life has played out in a way such that there have been prolonged periods of solitude, punctuated by skewed mix of necessary & unnecessary interactions with others. Having lived such a life, I think my mind loves anything that celebrates silence and solitude. No wonder that I could not put this book down, even while attending a conference. I took an immense liking to the book that I took every opportunity during the downtime between the talks at the conference, to lose myself in this book. One goes to a conference, not only to listen to what other people are doing in a specific field, but also to socialize. Just silently absorb the content of the talk and reflect on them. Somehow I found a strange kind of comforting feeling sitting amidst a random set of geeks and not talking to anyone. In this context, I remember something from the book Quiet, where Susan Cain says, her well groomed, well laid out office room that she had carefully prepared proved rather ineffective for writing. Instead, Starbucks outlets helped her in writing numerous drafts of the book. She says Starbucks has a unique feature, i.e. it is a place that is constantly buzzing with activity that gives a sense of community feeling and at the same time each one is minding one’s own work.

I read this book out of curiosity of finding out – What does a person who has been staying alone for twenty years got to say about solitude?

Sara Maitland’s house(a region of Scotland with one of the lowest population densities in Europe)

The author refers to her previous work “The Book on Silence” and says that she had mentioned a few things relevant to “Solitude” in it. She says that she has written this book mainly to expand those thoughts. Indeed silence and solitude healthily coexist. But there are situations where you are in silence without solitude / when you experience solitude without silence.

Being Alone in the Twenty-first century:

The first part of the book makes a case against the popular notion that seeking aloneness is not a pathological condition. Society tries to brand a person seeking alone time for an extended period of time as “sad, mad or bad”, or all the three at once. For a woman, it is even worse.

In the Middle Ages the word ‘spinster’ was a compliment. A spinster was someone, usually a woman, who could spin well: a woman who could spin well was financially self-sufficient – it was one of the very few ways that mediaeval women could achieve economic independence . The word was generously applied to all women at the point of marriage as a way of saying they came into the relationship freely, from personal choice, not financial desperation. Now it is an insult, because we fear ‘for’ such women – and now men as well – who are probably ‘sociopaths’.

Rebalancing Attitudes towards Solitude

The second part of the book gives a few ideas to strengthen your desire for and reduce your fear of solitude, ways in which you might, in practice, develop your taste for and skill at it. There are many people who actively avoid solitude. The two most common tactics for evading the terror of solitude are both singularly ineffective. The first is denigrating those who do not fear it, especially if they claim to enjoy it , and stereotyping them as ‘miserable’,‘selfish’,‘crazy’ or ‘perverse’ (sad, mad and bad). The second is infinitely extending our social contacts as a sort of insurance policy, which social media makes increasingly possible.

The book contains a set of guidelines that can be helpful in overturning negative views about solitude and developing a positive sense of aloneness and true capacity to enjoy it.

Face the fear

Do Something enjoyable alone : Have a balance between work time, maintenance time and leisure time.There is a good deal of anecdotal evidence that doing things alone intensifies the emotional experience; sharing an experience immediately appears to dissipate our emotional responses , as though communicating it drained away the visceral sensation.

Explore Reverie

Look at Nature

Learn something by heart

Wordsworth’s famous poem ‘Daffodils’ would have a very different effect if it ended:

For oft, when on my couch I lie In vacant or in pensive mood, I have to rise and go and search On Flickr, Google or YouTube.

The capacity to be creative is profoundly linked to the ability to remember: the word ‘remember’ derives from ‘re-member’, to ‘put the parts back together’. What we have memorized, learned by heart, we have internalized in a very special way. The knowledge is now part of our core self, our identity, and we can access it when we are alone: we are no longer an isolated fragment drifting in a huge void, but linked through these shared shards of culture to a larger, richer world, but without losing our ‘aloneness’. For many people this resource, this well-stocked mental larder, offers food for thought, for coherence, for security, and must be one of the factors that turns ‘isolation’ into creative solitude. This is a kind of cultural engagement that you cannot get from the web or from reading.

Going Solo : The author is not suggesting those “extreme adventures” that you can brag about to people around you. But something else. Read the book if you are curious.

The Joys of Solitude

The author writes about a few rewards that people who seek and experienced solitude have found :

A deeper consciousness of self: Behind the heavy sounding words, all it means that in solitude you know yourself better. Stripped of human interaction, you tend to be aware of your own feelings, thoughts, moods . How you deal with it is a different matter, but the very fact that you start noticing is itself a reward. People sometimes take all kinds of weird steps to experience conscious solitude in their lives. Here’s one such example of author’s friend, Jill Langford.

About twenty-five years into my marriage, with seven children, I asked my husband for a one-man tent for Christmas. A little taken aback, perhaps, he nonetheless granted my request and bought me a super little army tent or bivouac shell that you honestly couldn’t squeeze two people into. You erect it, quite easily and quickly, crawl in on your belly, then turn over onto your back, clutching a sleeping bag, raise your knees and wriggle your legs, then bottom, then torso into it. Et voilà. You stay in that position till morning, then you do the same in reverse. There is no room to sit up and you’d be a fool not to have a wee before retiring, since the whole procedure is well-nigh impossible in the middle of the night. I use this little tent just whenever I feel the need to take off, alone, for whatever reason. For me, it works like a battery charger when I feel weighed down by the burdens of living in community and am dragging my feet. Actually I don’t use it very much, but knowing it’s there to use if I want to is sometimes enough in itself to bring a spring back into my step.

Attunement to Nature: Over and over again individuals report these extraordinary, mystical experiences when they are alone in nature. It never seems to happen if you are with anyone else, perhaps because we all have a deep inhibition against exposing ourselves so nakedly to another, even a beloved other.

Relationship with God: If you are an atheist, it could just mean an entity beyond your sensory perception. There is no major religious or spiritual tradition that does not recognize solitude as a part of the necessary practice for revelation, intimacy and knowledge.

Creativity: We all have experienced at some point or the other—creativity somehow seems to go up when we are do things alone. We understand things better. We learn and experience things more deeply in solitude. Solitude is a well-established ‘school for genius’, and the outpouring of creativity is one of its promised joys. In learning to be solitary and happy with it, you can prepare yourself for this sort of creativity.

Freedom: There are two types of freedom, 1) “freedom from”, 2), ”freedom to”. In our society, the former is increasing becoming possible like freedom from poverty, pain or fear, financial insecurity etc. Solitude is associated with the latter kind of freedom

In The Stations of Solitude, the philosopher Alice Koller defined freedom as ‘Not only having no restraints, but also being self-governing according to laws of your own choosing … where your choices spring from a genuine sense of what your life is and can become.’ In this short passage she moves from ‘no restraints’ (freedom from) to being ‘self-governing’ (freedom to). In order to achieve this second sort of freedom she suggests that you need a ‘genuine sense of what your life is and can become’. That is to say, you need a consciousness of yourself, and we have already seen how solitude enhances and develops that self-awareness which is the first step towards being self-governing.

Being solitary is being alone well : being alone luxuriously immersed in doings of your own choice, aware of the fullness of your own presence rather than of the absence of others.

The book by Alex Kuznetsov gives a great overview of the financial markets in U.S. The book is targeted towards a person who is coming from a technical background and intends to work in finance but does not have a clear idea about,”What exactly happens on Wall Street ?” The book is ~ 500 pages and covers quite a lot of ground. The first part of the book gives a basic idea of how a Wall Street sell-side firm is structured, who are key players in the financial industry etc. The second part is the juiciest part of the book where the author covers all the main markets in US, with just enough content allocated to each market, that a curious reader will be enthused to read other books about them. The third part of the book deals with technology areas, and is priceless for a newbie quant at any Wall Street firm. The fourth part is too specific to people who probably see themselves as sys-admins.

The author is very clear about the target audience and hence highlights all the relevant aspects that a technical person who is looking for the “BIG PICTURE”, would immensely appreciate.